Regional population methodology

Latest release
Reference period
2022-23 financial year

Estimated resident population

Estimated resident population (ERP) is the official estimate of the Australian population, which links people to a place of usual residence within Australia. Usual residence is the address at which a person considers themselves to currently live. ERP includes all people who usually live in Australia (regardless of nationality, citizenship or legal status), with the exception of foreign diplomatic personnel and their families.

ERP, or population estimates, for Australia and it's states and territories (from now referred to as states) are prepared quarterly and released around six months after the reference date in National, state and territory population.

Annual population estimates as at 30 June are then prepared for areas below the state level and released in this product. Estimates are prepared at the Statistical Area Level 2 and Local Government Area levels, according to the Australian Statistical Geography Standard (ASGS), and are aggregated or split to create estimates for other geographies. Population estimates are available in this product for Statistical Areas Levels 2 to 4, Greater Capital City Statistical Areas, Local Government Areas, Significant Urban Areas, Remoteness Areas, and Commonwealth and State Electoral Divisions. 

Age and sex breakdowns of these estimates will be released on 29 August 2024 in Regional population by age and sex, 2023.

Method

ERP as at 30 June in a Census year is calculated by adjusting Census counts of Australian usual residents to account for residents temporarily overseas, people missed or counted more than once in the Census (based on the Post Enumeration Survey), and for the births, deaths and migration that happened between 30 June and Census night. 

At the national and state levels, ERP is updated from the Census base every three months by taking the population estimate at the start of the quarter and adding the components of population change: natural increase (births minus deaths), net overseas migration and (in the case of state populations) net interstate migration. This is known as the component method, and uses the demographic balancing equation:

\(P_{t+1}=P_t+B−D+NOM+NIM\) where:

\(P_t\) = the estimated resident population at time point \(t\)
\(P_{t+1}\) = the estimated resident population at time point \(t+1\)
\(B\) = the number of births occurring between \(t \) and \(t+1\)
\(D\) = the number of deaths occurring between \(t\) and \(t+1\)
\(NOM\) = net overseas migration occurring between \(t\) and \(t+1\)
\(NIM\) = net interstate migration occurring between \(t\) and \(t+1\)

At the national level, net interstate migration is zero.

For Statistical Areas Level 2 (SA2s) and Local Government Areas (LGAs), population estimates are updated from the Census base annually as at 30 June also using the component method. That is, by taking the estimate at the start of the financial year and adding natural increase and net overseas and internal (moves between and within the states) migration. The components for these sub-state areas are calculated by breaking down state-level component estimates, ensuring consistency between the state and sub-state population and component data.

The components of population change (and subsequently ERP) at the LGA level are constrained to those at the SA2 level to ensure consistency between these two geographies. This is done based on the smallest possible regions where SA2 and LGA boundaries match in terms of the combined area containing resident population. For example, where one LGA aligns exactly with one SA2 or where a group of LGAs aligns with a group of SA2s, the components for these areas will generally match. Estimates at the SA2 and LGA level are ultimately constrained so that they add to the relevant state estimates.

Once the estimates are updated, they are scrutinised and validated by ABS analysts. Local knowledge, such as that advised by state governments is considered and used to adjust data for particular SA2s and LGAs. In some small areas, population change since the previous Census is assumed to be zero in the absence of reliable component data.

To provide an indication of ERP below the SA2 level, population estimates are calculated for Statistical Areas Level 1 (SA1s). For a Census year, SA2 estimates are apportioned across SA1s using usual residence Census counts. In postcensal years, the SA2 estimates are apportioned across SA1s by taking into account population change implied by Medicare and electoral roll counts at the SA1 level. Estimates for SA1s are aggregated to regions such as Remoteness Areas. For areas that cannot be built up from whole SA1s, such as electoral divisions and Postal Areas, Mesh Block Census counts are used to estimate the share of the SA1 population that resides in those areas. By these means, population estimates for areas other than those provided in this product (including SA1s) may be available on request via the ABS website.

Rebasing

In Census years, both preliminary estimates (derived from updating ERP from the previous Census) and 'rebased' population estimates (based on the current Census) are prepared. Differences between these two sets of estimates are referred to as intercensal differences. Rebased estimates of SA2 populations for previous intercensal years are derived by apportioning the intercensal difference across the five years, while constraining to state totals. Rebased 2017 to 2020 estimates were generally derived by adding one-fifth of the 2021 intercensal difference to the previous estimate of the 2017 population, two-fifths to the previous estimate of the 2018 population, and so on. Intercensal difference was apportioned based on the unrebased growth rate for some areas (e.g. newly established areas). For further information, see Methodology used in final rebased population estimates, June 2021.

Accuracy

The sub-state estimates in this product are subject to some error. Some caution should be exercised when using the estimates, especially for areas with very small population.

The accuracy of ERP can be gauged by assessing the size and direction of intercensal differences. For Australia as at 30 June 2021, the unrebased ERP over-estimated the final rebased ERP by 0.2% (62,400 people). For the states and territories, the 2021 intercensal differences ranged from -3.7% (Tasmania) to +2.1% (Northern Territory).

To assess the quality of SA2-based estimates, unrebased estimates for 2021 were converted to SA2s based on ASGS Edition 3 boundaries, and constrained to final rebased state/territory ERP. These estimates were compared with final rebased 2021 SA2 estimates. The average of the absolute values of the intercensal differences for these SA2 estimates (excluding areas with less than 1,000 people) was 4.2%.

The table below shows that intercensal differences were generally larger for very small areas, and lower for very large areas.

Final intercensal differences, 2021
Size of SA2 (people)Number of SA2s (no.)Average absolute intercensal difference (%)
1,000 to 2,999948.9
3,000 to 4,9993053.9
5,000 to 6,9993283.7
7,000 to 9,9993974.0
10,000 to 14,9995944.3
15,000 to 19,9993843.9
20,000 and over2183.4

Status

To meet the competing demands for accuracy and timeliness, there are several versions of sub-state population estimates. Preliminary estimates are available around nine months after the reference date with revised estimates 12 months later. Rebased and final estimates are made available after each Census, when revisions are made to the estimates for all years in the previous intercensal period.

The status of annual sub-state ERP and components can change over time, from preliminary to revised to final, as new component data becomes available at the state level. With each release, ERP for the previous year is usually revised due to revisions to the component data at the state level. No updated sub-state data is used for these revisions. The table below shows the current status of sub-state ERP and the components of population change at the state level, for each year estimated out from the 2021 Census base. 

Current status of ERP and components
 Census baseNatural IncreaseOverseas migrationInterstate migrationERP status
June 20222021 CensusRevised - based on date of registrationRevised - based on modelled traveller behaviourPreliminary - based on expansion factors from the 2021 CensusRevised - updated due to revised component data at state level
June 20232021 CensusPreliminary - based on date of registrationPreliminary - based on modelled traveller behaviourPreliminary - based on expansion factors from the 2021 CensusPreliminary

The sub-state components of population change for 2016-17 to 2020-21 released in previous issues of this product will not be revised, and no longer sum to rebased population change for these years. 

Components of population change

Births and deaths

Natural increase (births minus deaths) for sub-state areas is calculated using information from each state/territory registry of births, deaths and marriages. The data is coded based on the place of usual residence of the mother for births, and the place of usual residence of the deceased for deaths. It is aggregated to SA2 and LGA levels and constrained to published state estimates of births and deaths.

The estimates of births and deaths in this product are prepared for financial years to correspond with the 30 June reference date for sub-state ERP. To produce timely sub-state estimates, preliminary births and deaths data are prepared using year of registration as a proxy for year of occurrence.

Preliminary births and deaths are prepared by breaking down preliminary state-level data. Later, when the state-level data is updated, the sub-state data is updated accordingly and released in the next issue of this product. 

The sub-state births and deaths data in this product are not coherent with the sub-state data released in Births, Australia and Deaths, Australia which are for calendar years and have a different scope.

Overseas migration

The movement of people from overseas to Australia's sub-state areas and vice-versa cannot be directly measured. It is estimated by breaking down overseas migrant arrivals and departures at the state level to sub-state areas, using information from the most recent Census. The state-level overseas migration data is sourced from Department of Home Affairs processing systems, visa information, and incoming passenger cards, and is published in National, state and territory population.

Regional overseas migration estimate (ROME) arrivals are estimated based on counts of people who were living overseas one year ago in the most recent Census, at SA2 level. For ROME arrivals for 2022 onwards, data from the 2016 Census was also used to account for low overseas arrivals in the 2021 Census due to the COVID-19 pandemic. These distributions are used to break down state arrivals each year up until the next Census. To account for changes to the census-based distribution of overseas arrivals within a state (e.g. in high growth or inner-city areas with changing numbers of temporary migrants), adjustments may be made based on up-to-date indicator data including counts of Temporary Skills Shortage visa holders and overseas students.

For ROME departures, a model distributes state-level overseas migrant departures to SA2s. This model is based on Census data on the number of overseas arrivals in the previous year and the proportion of population born overseas, and SEIFA score, for each SA2. Several models were evaluated with the model that best estimated population change between Censuses selected. As with ROME arrivals, ROME departures may be adjusted based on additional information sources.

LGA estimates of ROME arrivals and departures are prepared by converting from SA2-level ROME arrivals and departures, using a population-weighted correspondence.

Preliminary ROME arrivals and departures are prepared by breaking down preliminary state-level data. Later, when the state-level data is updated, the sub-state data is updated accordingly and released in the next issue of this product.

Internal migration

The movement of people between and within Australia's states cannot be directly measured and is estimated using administrative data. Internal migration is estimated based on a combination of Census data (usual address one year ago), Medicare change of address data (provided by Services Australia), and Department of Defence records (for military personnel only). 

Medicare is Australia's universal health insurance scheme and covers the vast majority of Australian residents. De-identified Medicare change of address counts are aggregated to SA2 and LGA levels. There are some people who are part of ERP but are not covered by Medicare, such as certain temporary visa holders. For others there is a time delay from when they move residence to when they update their address details with Medicare. To account for these issues, factors are applied to calibrate this data to internal migration data from the Census. These factors are applied by age, sex, state and move type (arrival or departure). Medicare data received for the year ending 30 September is used to estimate internal migration for the year ending 30 June. This assumes that on average, the time between a person moving house and registering their change of address with Medicare is three months. 

As many defence force personnel do not interact with Medicare, aggregated defence force personnel movements are converted from postcode and used to supplement the Medicare data. This data reflects the time of move and is therefore not lagged.

The Medicare and defence data are combined to prepare regional internal migration estimates (RIME) at SA2 and LGA levels. Interstate RIME moves are constrained to estimates of interstate migration as published in National, state and territory population.

RIME was previously prepared and released in Migration, Australia for financial years up to 2015-16. This old series of RIME was experimental in that it was prepared independently of and is not directly comparable with ERP nor with RIME prepared for 2016-17 onwards, due to different methods and source data used. 

Statistical geography

The Australian Statistical Geography Standard (ASGS) brings together all of the regions which the ABS and many other organisations use to collect, release and analyse geographically classified statistics. The ASGS classification structures are split into two broad groups, ABS Structures and Non-ABS Structures.

The ABS Structures are defined and maintained by the ABS, and remain unchanged for the five years between Censuses. Further information on the ABS Structures for which estimates are available in this product is contained in: 

The Non-ABS Structures are not defined or maintained by the ABS, and generally represent administrative regions. Further information on the Non-ABS Structures for which population estimates are available in this product is contained in:

As the Non-ABS Structures represent regions that are subject to ongoing change, the ABS releases updates to these Structures each year where significant change has occurred. The following table summarises the Non-ABS Structures that data is released for in this product:

Non-ABS Structures in this product
Non-ABS StructureBoundaries
Local Government Areas2023
Commonwealth Electoral Divisions2021
State Electoral Divisions2022

Maps of the statistical areas defined in the ASGS are available in the online mapping tool ABS Maps.

The area figures used in this product were calculated using ABS standard Geographic Information System software from the digital boundaries of the ASGS. 

Local Government Area changes

When boundaries for Non-ABS Structures such as Local Government Areas (LGAs) change, historical population estimates for these new boundaries are prepared to enable the comparison of regional populations over time. There were no changes to LGA boundaries that involved population between 2022 and 2023.

Other population measures

Centre of population

The centre of population of a region is a point used to summarise the spatial distribution of a population and is calculated in this product based on SA1s. Due to the inherent imprecision in small area estimates, the centre of population should be considered indicative and not ascribed to an exact location. The use of different geographical level data in the calculation of the centre of population can result in different locations.

Population density

The population density of each region in this product has been calculated by dividing its ERP by its area in square kilometres. The result is expressed as a number of people per square kilometre.

Population grid

In this product, ERP is also presented in one square kilometre grid format. The population grid offers a consistently sized spatial unit and gives a refined model of population distribution, particularly for the non-urban areas of Australia. It is also an established, easy to understand and readily comparable international standard which enables users to make local, national and international comparisons of population density.

The population grid is prepared using SA1 population estimates. Within each populated SA1, all known residential dwelling locations were identified using a subset of the ABS Address Register, and the population distributed equally across the residential dwellings. The average value assigned to each dwelling was then summed within each one square kilometre grid cell across the country. This is modelled data and caution must be used in its interpretation, as the population has not been measured at the one square kilometre grid cell level.

Prior to 2021, the grid was prepared using known residential dwelling locations based on the Geocoded National Address File. The new methodology used for 2021 onward, which makes use of the ABS Address Register, has resulted in the population grid showing a more targeted representation of the population.

The population grid is provided in ESRI Grid format and Geo TIFF format, which are recommended for users proficient in the use of Geographic Information System software.

Confidentiality

The ABS collects statistical information under the authority of the Census and Statistics Act, 1905. This requires that statistical output shall not be published or disseminated in a manner that is likely to enable the identification of a particular person or organisation.

To guard against identification or disclosure of confidential information, a procedure is applied to confidentialise sub-state ERP and components, which are also subsequently constrained so that they add to relevant state estimates. As a result of this confidentialisation method, and forced additivity, estimates of under three people should be regarded as synthetic and only exist to ensure additivity to higher levels.

ABS statistics draw extensively on information provided freely by individuals, businesses, governments and other organisations. Their continued cooperation is very much appreciated: without it, the wide range of statistics published by the ABS would not be available. Information received by the ABS is treated in strict confidence as required by the Census and Statistics Act 1905.

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